Extracting trip demand for static demand responsive transit service based on taxi trips

Zheyu Li; Hui Jin; Xiaoguang Yang; Hanxuan Fang

doi:10.1117/12.3054737

20 December 2024 Extracting trip demand for static demand responsive transit service based on taxi trips

Zheyu Li, Hui Jin, Xiaoguang Yang, Hanxuan Fang

Author Affiliations +

Proceedings Volume 13421, Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024); 134211U (2024) https://doi.org/10.1117/12.3054737
Event: Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), 2024, Dalian, China

Abstract

Static demand-responsive transit (SDRT) is an innovative service model, which provides public transport services for passengers who have similar origin and destination locations, and departure time for a certain period at generally higher price. This paper proposes a method to extract potential trip demand for SDRT from taxi order data. Passenger OD flow similarity is analysed from the perspective of spatial and geometric features, including the parameters of spatial geography, trip distance, and trip angle. OD flow similarity function is constructed, which serves as the clustering criterion within a K-nearest neighbour agglomerative hierarchical clustering framework. Thus we may locate the potential passenger OD demand to direct the efficient design of SDRT route. A case study is conducted based on taxi order data collected in Suzhou, China over one day, where the proposed method manages to extract the potential passenger demand of 22 clusters for profitable SDRT.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zheyu Li, Hui Jin, Xiaoguang Yang, and Hanxuan Fang "Extracting trip demand for static demand responsive transit service based on taxi trips", Proc. SPIE 13421, Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), 134211U (20 December 2024); https://doi.org/10.1117/12.3054737

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE